The greatest value of a picture is when it forces us to notice what we never expected to see.
seaborn plotsMany, many more in these categories - these are just our focus for today!
import pandas as pd
mx_csv = "http://personal.tcu.edu/kylewalker/mexico.csv"
mx = pd.read_csv(mx_csv)
mx.head()How about sorting our data?
seabornseabornzac = mx[mx.name == 'Zacatecas'].drop(['name', 'FID', 'gdp08', 'mus09'], axis = 1).squeeze()
zac.name = 'Zacatecas'
zac.plot(kind = 'pie', figsize = (6, 6))pandashs_drop = pd.read_csv('http://personal.tcu.edu/kylewalker/data/hs_drop.csv')
hs_drop.sort_values('year', inplace = True)
hs_drop.set_index('year', inplace = True)
hs_drop.plot() # pandas plotting defaults to line charts, infers x from indexpandasseabornlmplot and regplot functionspandas: .corr()